astro-ph.IM - 仪器仪表和天体物理学方法

    cs.AI - 人工智能 cs.CE - 计算工程、 金融和科学 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.DM - 离散数学 cs.DS - 数据结构与算法 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.OS - 操作系统 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.ST - 统计理论 physics.soc-ph - 物理学与社会 q-bio.QM - 定量方法 q-fin.CP -计算金融学 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [astro-ph.IM]Carving out the low surface brightness universe with NoiseChisel
    • [cs.AI]Active Goal Recognition
    • [cs.AI]An Extensible and Personalizable Multi-Modal Trip Planner
    • [cs.AI]Dynamically Pruned Message Passing Networks for Large-Scale Knowledge Graph Reasoning
    • [cs.AI]Temporal Planning with Intermediate Conditions and Effects
    • [cs.CE]Scalable Simulation of Realistic Volume Fraction Red Blood Cell Flows through Vascular Networks
    • [cs.CL]Annotated Guidelines and Building Reference Corpus for Myanmar-English Word Alignment
    • [cs.CL]Atalaya at TASS 2019: Data Augmentation and Robust Embeddings for Sentiment Analysis
    • [cs.CL]Attention Interpretability Across NLP Tasks
    • [cs.CL]Breaking the Data Barrier: Towards Robust Speech Translation via Adversarial Stability Training
    • [cs.CL]Developing a Fine-Grained Corpus for a Less-resourced Language: the case of Kurdish
    • [cs.CL]Diachronic Topics in New High German Poetry
    • [cs.CL]Learning A Unified Named Entity Tagger From Multiple Partially Annotated Corpora For Efficient Adaptation
    • [cs.CL]Learning to Detect Opinion Snippet for Aspect-Based Sentiment Analysis
    • [cs.CL]Multi-Dimensional Explanation of Reviews
    • [cs.CL]PaRe: A Paper-Reviewer Matching Approach Using a Common Topic Space
    • [cs.CL]Question Answering is a Format; When is it Useful?
    • [cs.CL]Semi-supervised Text Style Transfer: Cross Projection in Latent Space
    • [cs.CL]Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph Completion
    • [cs.CL]TalkDown: A Corpus for Condescension Detection in Context
    • [cs.CL]Task-Oriented Conversation Generation Using Heterogeneous Memory Networks
    • [cs.CR]Ethical Hacking for IoT Security: A First Look into Bug Bounty Programs and Responsible Disclosure
    • [cs.CR]On Locally Decodable Codes in Resource Bounded Channels
    • [cs.CV]A closer look at domain shift for deep learning in histopathology
    • [cs.CV]Accurate and Compact Convolutional Neural Networks with Trained Binarization
    • [cs.CV]Anchor Loss: Modulating Loss Scale based on Prediction Difficulty
    • [cs.CV]Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization
    • [cs.CV]Balancing Specialization, Generalization, and Compression for Detection and Tracking
    • [cs.CV]Beyond image classification: zooplankton identification with deep vector space embeddings
    • [cs.CV]CAT: Compression-Aware Training for bandwidth reduction
    • [cs.CV]Conditional Transferring Features: Scaling GANs to Thousands of Classes with 30% Less High-quality Data for Training
    • [cs.CV]Cross-View Kernel Similarity Metric Learning Using Pairwise Constraints for Person Re-identification
    • [cs.CV]Deep Learning for Deepfakes Creation and Detection
    • [cs.CV]Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation
    • [cs.CV]Efficient Residual Dense Block Search for Image Super-Resolution
    • [cs.CV]FALCON: Fast and Lightweight Convolution for Compressing and Accelerating CNN
    • [cs.CV]Gated Channel Transformation for Visual Recognition
    • [cs.CV]Guided Attention Network for Object Detection and Counting on Drones
    • [cs.CV]IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks
    • [cs.CV]Learning Propagation for Arbitrarily-structured Data
    • [cs.CV]MIC: Mining Interclass Characteristics for Improved Metric Learning
    • [cs.CV]Multi-modal segmentation with missing MR sequences using pre-trained fusion networks
    • [cs.CV]Multi-scale discriminative Region Discovery for Weakly-Supervised Object Localization
    • [cs.CV]Pretraining boosts out-of-domain robustness for pose estimation
    • [cs.CV]Rescan: Inductive Instance Segmentation for Indoor RGBD Scans
    • [cs.CV]Stochastic Conditional Generative Networks with Basis Decomposition
    • [cs.CV]The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery
    • [cs.CV]Towards Automated Biometric Identification of Sea Turtles (Chelonia mydas)
    • [cs.CV]Unsupervised Deep Features for Privacy Image Classification
    • [cs.CY]Usefulness of Instructor Annotations on Flipped Learning Preparation Video System
    • [cs.DC]BlendSM-DDM: BLockchain-ENabled Secure Microservices for Decentralized Data Marketplaces
    • [cs.DC]Design Methodology for Energy Efficient Unmanned Aerial Vehicles
    • [cs.DC]Message Scheduling for Performant, Many-Core Belief Propagation
    • [cs.DC]Prism: Scaling Bitcoin by 10,000x
    • [cs.DC]Scalable and Efficient Data Authentication for Decentralized Systems
    • [cs.DC]Scheduling on Two Types of Resources: a Survey
    • [cs.DL]Understanding the Twitter Usage of Science Citation Index (SCI) Journals
    • [cs.DM]Random $k$-out subgraph leaves only $O(n/k)$ inter-component edges
    • cs.DS Sample-Optimal Sparse Fourier Transform in Any Dimension; RIPless and Filterless
    • [cs.HC]EEG-Based Driver Drowsiness Estimation Using Feature Weighted Episodic Training
    • [cs.IR]Neighborhood-Enhanced and Time-Aware Model for Session-based Recommendation
    • [cs.IT]Blind Channel Estimation and Data Detection with Unknown Modulation and Coding Scheme
    • [cs.IT]Context-Aware Decentralized Invariant Signaling for Opportunistic Communications
    • [cs.IT]Energy Efficiency Maximization Via Joint Sub-Carrier Assignment and Power Control for OFDMA Full Duplex Networks
    • [cs.IT]Multiple-Rate Channel Codes in $\texttt{GF}(p{2}})$
    • [cs.IT]On the Contact and Nearest-Neighbor Distance Distributions for the n-Dimensional Matern Cluster Process
    • [cs.IT]On the Information Leakage in Private Information Retrieval Systems
    • [cs.IT]One-shot achievability and converse bounds of Gaussian random coding in AWGN channels under covert constraints
    • [cs.IT]Power-Imbalanced Low-Density Signatures (LDS) From Eisenstein Numbers
    • [cs.IT]Three Dimensional Sums of Character Gabor Systems
    • [cs.LG]A Self-consistent-field Iteration for Orthogonal Canonical Correlation Analysis
    • [cs.LG]Adversarial Variational Domain Adaptation
    • [cs.LG]Asymptotics of Wide Networks from Feynman Diagrams
    • [cs.LG]Attention-based Deep Tropical Cyclone Rapid Intensification Prediction
    • [cs.LG]Avoidance Learning Using Observational Reinforcement Learning
    • [cs.LG]CLN2INV: Learning Loop Invariants with Continuous Logic Networks
    • [cs.LG]Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network
    • [cs.LG]Decoder Choice Network for Meta-Learning
    • [cs.LG]Deep Generative Model for Sparse Graphs using Text-Based Learning with Augmentation in Generative Examination Networks
    • [cs.LG]Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders
    • [cs.LG]Domain-invariant Learning using Adaptive Filter Decomposition
    • [cs.LG]Exascale Deep Learning for Scientific Inverse Problems
    • [cs.LG]Gap Aware Mitigation of Gradient Staleness
    • [cs.LG]Graph Neural Reasoning May Fail in Proving Boolean Unsatisfiability
    • [cs.LG]Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting
    • [cs.LG]HaarPooling: Graph Pooling with Compressive Haar Basis
    • [cs.LG]IFR-Net: Iterative Feature Refinement Network for Compressed Sensing MRI
    • [cs.LG]Input complexity and out-of-distribution detection with likelihood-based generative models
    • [cs.LG]Learning in the Machine: To Share or Not to Share?
    • [cs.LG]Matrix Sketching for Secure Collaborative Machine Learning
    • [cs.LG]Mining Human Mobility Data to Discover Locations and Habits
    • [cs.LG]Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models
    • [cs.LG]Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
    • [cs.LG]Modular Deep Reinforcement Learning with Temporal Logic Specifications
    • [cs.LG]Neural networks are $\textit{a priori}$ biased towards Boolean functions with low entropy
    • [cs.LG]Off-Policy Actor-Critic with Shared Experience Replay
    • [cs.LG]On Understanding Knowledge Graph Representation
    • [cs.LG]Online Non-Monotone DR-submodular Maximization
    • [cs.LG]Online Semi-Supervised Concept Drift Detection with Density Estimation
    • [cs.LG]PCMC-Net: Feature-based Pairwise Choice Markov Chains
    • [cs.LG]Pre-training as Batch Meta Reinforcement Learning with tiMe
    • [cs.LG]PyDEns: a Python Framework for Solving Differential Equations with Neural Networks
    • [cs.LG]Reducing Transformer Depth on Demand with Structured Dropout
    • [cs.LG]Regularising Deep Networks with DGMs
    • [cs.LG]Scale-Equivariant Neural Networks with Decomposed Convolutional Filters
    • [cs.LG]Semi-supervised classification on graphs using explicit diffusion dynamics
    • [cs.LG]Sign Language Recognition Analysis using Multimodal Data
    • [cs.LG]Supervised Vector Quantized Variational Autoencoder for Learning Interpretable Global Representations
    • [cs.LG]Switched linear projections and inactive state sensitivity for deep neural network interpretability
    • [cs.LG]Synthetic Data for Deep Learning
    • [cs.LG]Teacher-Student Learning Paradigm for Tri-training: An Efficient Method for Unlabeled Data Exploitation
    • [cs.LG]The Dynamical Gaussian Process Latent Variable Model in the Longitudinal Scenario
    • [cs.LG]When to Intervene: Detecting Abnormal Mood using Everyday Smartphone Conversations
    • [cs.LG]Wider Networks Learn Better Features
    • [cs.MA]$α^α$-Rank: Scalable Multi-agent Evaluation through Evolution
    • [cs.NE]Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space
    • [cs.NE]Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network
    • [cs.NI]20 Years of Evolution from Cognitive to Intelligent Communications
    • [cs.NI]A Predictive On-Demand Placement of UAV Base Stations Using Echo State Network
    • [cs.OS]SIVSHM: Secure Inter-VM Shared Memory
    • [cs.RO]ARCSnake: An Archimedes’ Screw-Propelled, Reconfigurable Robot Snake for Complex Environments
    • [cs.RO]Accept Synthetic Objects as Real: End-to-End Training of Attentive Deep Visuomotor Policies for Manipulation in Clutter
    • [cs.RO]Automatic Snake Gait Generation Using Model Predictive Control
    • [cs.RO]C-3PO: Cyclic-Three-Phase Optimization for Human-Robot Motion Retargeting based on Reinforcement Learning
    • [cs.RO]CAGE: Context-Aware Grasping Engine
    • [cs.RO]Contact-Aware Controller Design for Complementarity Systems
    • [cs.RO]Deep Dynamics Models for Learning Dexterous Manipulation
    • [cs.RO]Human-in-the-loop Robotic Manipulation Planning for Collaborative Assembly
    • [cs.RO]Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller
    • [cs.RO]Leveraging the Template and Anchor Framework for Safe, Online Robotic Gait Design
    • [cs.RO]Minimal Work: A Grasp Quality Metric for Deformable Hollow Objects
    • [cs.RO]Modeling and Experimental Validation of the Mechanics of a Wheeled Non-Holonomic Robot Capable of Enabling Homeostasis
    • [cs.RO]Motion Estimation in Occupancy Grid Maps in Stationary Settings Using Recurrent Neural Networks
    • [cs.RO]Negotiation-based Human-Robot Collaboration via Augmented Reality
    • [cs.RO]OCTNet: Trajectory Generation in New Environments from Past Experiences
    • [cs.RO]Probabilistic Data Association via Mixture Models for Robust Semantic SLAM
    • [cs.RO]ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots
    • [cs.RO]Robust Semi-Direct Monocular Visual Odometry Using Edge and Illumination-Robust Cost
    • [cs.RO]Towards Variable Assistance for Lower Body Exoskeletons
    • [cs.SD]High Fidelity Speech Synthesis with Adversarial Networks
    • [cs.SD]HumanGAN: generative adversarial network with human-based discriminator and its evaluation in speech perception modeling
    • [cs.SE]Software Engineering Meets Deep Learning: A Literature Review
    • [cs.SI]Decentralized Trust Management: Risk Analysis and Trust Aggregation
    • [cs.SI]Mining user interaction patterns in the darkweb to predict enterprise cyber incidents
    • [eess.AS]Improving Robustness In Speaker Identification Using A Two-Stage Attention Model
    • [eess.IV]Augmenting the Pathology Lab: An Intelligent Whole Slide Image Classification System for the Real World
    • [eess.IV]Automated identification of neural cells in the multi-photon images using deep-neural networks
    • [eess.IV]Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging
    • [eess.IV]Deep learning vessel segmentation and quantification of the foveal avascular zone using commercial and prototype OCT-A platforms
    • [eess.IV]Deformable Non-local Network For Video Super-Resolution
    • [eess.IV]Intelligent image synthesis to attack a segmentation CNN using adversarial learning
    • [eess.IV]Non-imaging single-pixel sensing with optimized binary modulation
    • [eess.IV]Towards continuous learning for glioma segmentation with elastic weight consolidation
    • [eess.IV]mustGAN: Multi-Stream Generative Adversarial Networks for MR Image Synthesis
    • [eess.SP]Optimally Compressed Nonparametric Online Learning
    • [eess.SY]Efficient Multi-Agent Trajectory Planning with Feasibility Guarantee using Relative Bernstein Polynomial
    • [math.ST]Exact confidence interval for generalized Flajolet-Martin algorithms
    • [math.ST]Stationarity and Moment Properties of some Multivariate Count Autoregressions
    • [physics.soc-ph]Inequality is rising where social network segregation interacts with urban topology
    • [physics.soc-ph]Mobile Phone Data for Children on the Move: Challenges and Opportunities
    • [q-bio.QM]Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile health data
    • [q-fin.CP]Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimensions
    • [quant-ph]Practical route to entanglement-enhanced communication over noisy bosonic channels
    • [stat.AP]Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis
    • [stat.AP]Selecting a Scale for Spatial Confounding Adjustment
    • [stat.CO]Real time analysis of epidemic data
    • [stat.ME]Survival analysis as a classification problem
    • [stat.ME]Testing for Association in Multi-View Network Data
    • [stat.ML]A Generative Model for Molecular Distance Geometry
    • [stat.ML]Classification Logit Two-sample Testing by Neural Networks
    • [stat.ML]Determining offshore wind installation times using machine learning and open data
    • [stat.ML]Hierarchical Probabilistic Model for Blind Source Separation via Legendre Transformation
    • [stat.ML]Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi’s Entropy and Tensor Kernels
    • [stat.ML]Modelling the influence of data structure on learning in neural networks
    • [stat.ML]Simple and Almost Assumption-Free Out-of-Sample Bound for Random Feature Mapping
    • [stat.ML]Structured Graph Learning Via Laplacian Spectral Constraints

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    • [astro-ph.IM]Carving out the low surface brightness universe with NoiseChisel
    Mohammad Akhlaghi
    http://arxiv.org/abs/1909.11230v1

    • [cs.AI]Active Goal Recognition
    Christopher Amato, Andrea Baisero
    http://arxiv.org/abs/1909.11173v1

    • [cs.AI]An Extensible and Personalizable Multi-Modal Trip Planner
    Xudong Liu, Christian Fritz, Matthew Klenk
    http://arxiv.org/abs/1909.11604v1

    • [cs.AI]Dynamically Pruned Message Passing Networks for Large-Scale Knowledge Graph Reasoning
    Xiaoran Xu, Wei Feng, Yunsheng Jiang, Xiaohui Xie, Zhiqing Sun, Zhi-Hong Deng
    http://arxiv.org/abs/1909.11334v1

    • [cs.AI]Temporal Planning with Intermediate Conditions and Effects
    Alessandro Valentini, Andrea Micheli, Alessandro Cimatti
    http://arxiv.org/abs/1909.11581v1

    • [cs.CE]Scalable Simulation of Realistic Volume Fraction Red Blood Cell Flows through Vascular Networks
    Libin Lu, Matthew J. Morse, Abtin Rahimian, Georg Stadler, Denis Zorin
    http://arxiv.org/abs/1909.11085v1

    • [cs.CL]Annotated Guidelines and Building Reference Corpus for Myanmar-English Word Alignment
    Nway Nway Han, Aye Thida
    http://arxiv.org/abs/1909.11288v1

    • [cs.CL]Atalaya at TASS 2019: Data Augmentation and Robust Embeddings for Sentiment Analysis
    Franco M. Luque
    http://arxiv.org/abs/1909.11241v1

    • [cs.CL]Attention Interpretability Across NLP Tasks
    Shikhar Vashishth, Shyam Upadhyay, Gaurav Singh Tomar, Manaal Faruqui
    http://arxiv.org/abs/1909.11218v1

    • [cs.CL]Breaking the Data Barrier: Towards Robust Speech Translation via Adversarial Stability Training
    Qiao Cheng, Meiyuan Fang, Yaqian Han, Jin Huang, Yitao Duan
    http://arxiv.org/abs/1909.11430v1

    • [cs.CL]Developing a Fine-Grained Corpus for a Less-resourced Language: the case of Kurdish
    Roshna Omer Abdulrahman, Hossein Hassani, Sina Ahmadi
    http://arxiv.org/abs/1909.11467v1

    • [cs.CL]Diachronic Topics in New High German Poetry
    Thomas N. Haider
    http://arxiv.org/abs/1909.11189v1

    • [cs.CL]Learning A Unified Named Entity Tagger From Multiple Partially Annotated Corpora For Efficient Adaptation
    Xiao Huang, Li Dong, Elizabeth Boschee, Nanyun Peng
    http://arxiv.org/abs/1909.11535v1

    • [cs.CL]Learning to Detect Opinion Snippet for Aspect-Based Sentiment Analysis
    Mengting Hu, Shiwan Zhao, Honglei Guo, Renhong Cheng, Zhong Su
    http://arxiv.org/abs/1909.11297v1

    • [cs.CL]Multi-Dimensional Explanation of Reviews
    Diego Antognini, Claudiu Musat, Boi Faltings
    http://arxiv.org/abs/1909.11386v1

    • [cs.CL]PaRe: A Paper-Reviewer Matching Approach Using a Common Topic Space
    Omer Anjum, Hongyu Gong, Suma Bhat, Wen-Mei Hwu, Jinjun Xiong
    http://arxiv.org/abs/1909.11258v1

    • [cs.CL]Question Answering is a Format; When is it Useful?
    Matt Gardner, Jonathan Berant, Hannaneh Hajishirzi, Alon Talmor, Sewon Min
    http://arxiv.org/abs/1909.11291v1

    • [cs.CL]Semi-supervised Text Style Transfer: Cross Projection in Latent Space
    Mingyue Shang, Piji Li, Zhenxin Fu, Lidong Bing, Dongyan Zhao, Shuming Shi, Rui Yan
    http://arxiv.org/abs/1909.11493v1

    • [cs.CL]Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph Completion
    Zihao Wang, Kwun Ping Lai, Piji Li, Lidong Bing, Wai Lam
    http://arxiv.org/abs/1909.11359v1

    • [cs.CL]TalkDown: A Corpus for Condescension Detection in Context
    Zijian Wang, Christopher Potts
    http://arxiv.org/abs/1909.11272v1

    • [cs.CL]Task-Oriented Conversation Generation Using Heterogeneous Memory Networks
    Zehao Lin, Xinjing Huang, Feng Ji, Haiqing Chen, Ying Zhang
    http://arxiv.org/abs/1909.11287v1

    • [cs.CR]Ethical Hacking for IoT Security: A First Look into Bug Bounty Programs and Responsible Disclosure
    Aaron Yi Ding, Gianluca Limon De Jesus, Marijn Janssen
    http://arxiv.org/abs/1909.11166v1

    • [cs.CR]On Locally Decodable Codes in Resource Bounded Channels
    Jeremiah Blocki, Shubhang Kulkarni, Samson Zhou
    http://arxiv.org/abs/1909.11245v1

    • [cs.CV]A closer look at domain shift for deep learning in histopathology
    Karin Stacke, Gabriel Eilertsen, Jonas Unger, Claes Lundström
    http://arxiv.org/abs/1909.11575v1

    • [cs.CV]Accurate and Compact Convolutional Neural Networks with Trained Binarization
    Zhe Xu, Ray C. C. Cheung
    http://arxiv.org/abs/1909.11366v1

    • [cs.CV]Anchor Loss: Modulating Loss Scale based on Prediction Difficulty
    Serim Ryou, Seong-Gyun Jeong, Pietro Perona
    http://arxiv.org/abs/1909.11155v1

    • [cs.CV]Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization
    Ruyi Ji, Longyin Wen, Libo Zhang, Dawei Du, Ynajun Wu, Chen Zhao, Xianglong Liu, Feiyue Huang
    http://arxiv.org/abs/1909.11378v1

    • [cs.CV]Balancing Specialization, Generalization, and Compression for Detection and Tracking
    Dotan Kaufman, Koby Bibas, Eran Borenstein, Michael Chertok, Tal Hassner
    http://arxiv.org/abs/1909.11348v1

    • [cs.CV]Beyond image classification: zooplankton identification with deep vector space embeddings
    Ketil Malde, Hyeongji Kim
    http://arxiv.org/abs/1909.11380v1

    • [cs.CV]CAT: Compression-Aware Training for bandwidth reduction
    Chaim Baskin, Brian Chmiel, Evgenii Zheltonozhskii, Ron Banner, Alex M. Bronstein, Avi Mendelson
    http://arxiv.org/abs/1909.11481v1

    • [cs.CV]Conditional Transferring Features: Scaling GANs to Thousands of Classes with 30% Less High-quality Data for Training
    Chunpeng Wu, Wei Wen, Yiran Chen, Hai Li
    http://arxiv.org/abs/1909.11308v1

    • [cs.CV]Cross-View Kernel Similarity Metric Learning Using Pairwise Constraints for Person Re-identification
    T M Feroz Ali, Subhasis Chaudhuri
    http://arxiv.org/abs/1909.11316v1

    • [cs.CV]Deep Learning for Deepfakes Creation and Detection
    Thanh Thi Nguyen, Cuong M. Nguyen, Dung Tien Nguyen, Duc Thanh Nguyen, Saeid Nahavandi
    http://arxiv.org/abs/1909.11573v1

    • [cs.CV]Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation
    Xianxu Hou, Jingxin Liu, Bolei Xu, Bozhi Liu, Xin Chen, Mohammad Ilyas, Ian Ellis, Jon Garibaldi, Guoping Qiu
    http://arxiv.org/abs/1909.11524v1

    • [cs.CV]Efficient Residual Dense Block Search for Image Super-Resolution
    Dehua Song, Chang Xu, Xu Jia, Chunjing Xu, Yunhe Wang
    http://arxiv.org/abs/1909.11409v1

    • [cs.CV]FALCON: Fast and Lightweight Convolution for Compressing and Accelerating CNN
    Chun Quan, Jun-Gi Jang, Hyun Dong Lee, U Kang
    http://arxiv.org/abs/1909.11321v1

    • [cs.CV]Gated Channel Transformation for Visual Recognition
    Zongxin Yang, Linchao Zhu, Yu Wu, Yi Yang
    http://arxiv.org/abs/1909.11519v1

    • [cs.CV]Guided Attention Network for Object Detection and Counting on Drones
    Yuanqiang Cai, Dawei Du, Libo Zhang, Longyin Wen, Weiqiang Wang, Yanjun Wu, Siwei Lyu
    http://arxiv.org/abs/1909.11307v1

    • [cs.CV]IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks
    Haotong Qin, Ruihao Gong, Xianglong Liu, Ziran Wei, Fengwei Yu, Jingkuan Song
    http://arxiv.org/abs/1909.10788v2

    • [cs.CV]Learning Propagation for Arbitrarily-structured Data
    Sifei Liu, Xueting Li, Varun Jampani, Shalini De Mello, Jan Kautz
    http://arxiv.org/abs/1909.11237v1

    • [cs.CV]MIC: Mining Interclass Characteristics for Improved Metric Learning
    Karsten Roth, Biagio Brattoli, Björn Ommer
    http://arxiv.org/abs/1909.11574v1

    • [cs.CV]Multi-modal segmentation with missing MR sequences using pre-trained fusion networks
    Karin van Garderen, Marion Smits, Stefan Klein
    http://arxiv.org/abs/1909.11464v1

    • [cs.CV]Multi-scale discriminative Region Discovery for Weakly-Supervised Object Localization
    Pei Lv, Haiyu Yu, Junxiao Xue, Junjin Cheng, Lisha Cui, Bing Zhou, Mingliang Xu, Yi Yang
    http://arxiv.org/abs/1909.10698v1

    • [cs.CV]Pretraining boosts out-of-domain robustness for pose estimation
    Alexander Mathis, Mert Yüksekgönül, Byron Rogers, Matthias Bethge, Mackenzie W. Mathis
    http://arxiv.org/abs/1909.11229v1

    • [cs.CV]Rescan: Inductive Instance Segmentation for Indoor RGBD Scans
    Maciej Halber, Yifei Shi, Kai Xu, Thomas Funkhouser
    http://arxiv.org/abs/1909.11268v1

    • [cs.CV]Stochastic Conditional Generative Networks with Basis Decomposition
    Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
    http://arxiv.org/abs/1909.11286v1

    • [cs.CV]The Good, the Bad and the Ugly: Evaluating Convolutional Neural Networks for Prohibited Item Detection Using Real and Synthetically Composited X-ray Imagery
    Neelanjan Bhowmik, Qian Wang, Yona Falinie A. Gaus, Marcin Szarek, Toby P. Breckon
    http://arxiv.org/abs/1909.11508v1

    • [cs.CV]Towards Automated Biometric Identification of Sea Turtles (Chelonia mydas)
    Irwandi Hipiny, Hamimah Ujir, Aazani Mujahid, Nurhartini Kamalia Yahya
    http://arxiv.org/abs/1909.11277v1

    • [cs.CV]Unsupervised Deep Features for Privacy Image Classification
    Chiranjibi Sitaula, Yong Xiang, Sunil Aryal, Xuequan Lu
    http://arxiv.org/abs/1909.10708v1

    • [cs.CY]Usefulness of Instructor Annotations on Flipped Learning Preparation Video System
    Shintaro Uchiyama, Hayato Okumoto, Mitsuo Yoshida, Yuko Ichikawa, Kyoji Umemura
    http://arxiv.org/abs/1909.11341v1

    • [cs.DC]BlendSM-DDM: BLockchain-ENabled Secure Microservices for Decentralized Data Marketplaces
    Ronghua Xu, Gowri Sankar Ramachandran, Yu Chen, Bhaskar Krishnamachari
    http://arxiv.org/abs/1909.10888v1

    • [cs.DC]Design Methodology for Energy Efficient Unmanned Aerial Vehicles
    Jingyu He, Yao Xiao, Paul Bogdan, Corina Bogdan
    http://arxiv.org/abs/1909.11238v1

    • [cs.DC]Message Scheduling for Performant, Many-Core Belief Propagation
    Mark Van der Merwe, Vinu Joseph, Ganesh Gopalakrishnan
    http://arxiv.org/abs/1909.11469v1

    • [cs.DC]Prism: Scaling Bitcoin by 10,000x
    Lei Yang, Vivek Bagaria, Gerui Wang, Mohammad Alizadeh, David Tse, Giulia Fanti, Pramod Viswanath
    http://arxiv.org/abs/1909.11261v1

    • [cs.DC]Scalable and Efficient Data Authentication for Decentralized Systems
    Soujanya Ponnapalli, Aashaka Shah, Amy Tai, Souvik Banerjee, Vijay Chidambaram, Dahlia Malkhi, Michael Wei
    http://arxiv.org/abs/1909.11590v1

    • [cs.DC]Scheduling on Two Types of Resources: a Survey
    Olivier Beaumont, Louis-claude Canon, Lionel Eyraud-Dubois, Giorgio Lucarelli, Loris Marchal, Clément Mommessin, Bertrand Simon, Denis Trystram
    http://arxiv.org/abs/1909.11365v1

    • [cs.DL]Understanding the Twitter Usage of Science Citation Index (SCI) Journals
    Aravind Sesagiri Raamkumar, Mojisola Erdt, Harsha Vijayakumar, Aarthy Nagarajan, Yin-Leng Theng
    http://arxiv.org/abs/1909.11340v1

    • [cs.DM]Random $k$-out subgraph leaves only $O(n/k)$ inter-component edges
    Jacob Holm, Valerie King, Mikkel Thorup, Or Zamir, Uri Zwick
    http://arxiv.org/abs/1909.11147v1

    • [cs.DS](Nearly) Sample-Optimal Sparse Fourier Transform in Any Dimension; RIPless and Filterless
    Vasileios Nakos, Zhao Song, Zhengyu Wang
    http://arxiv.org/abs/1909.11123v1

    • [cs.HC]EEG-Based Driver Drowsiness Estimation Using Feature Weighted Episodic Training
    Yuqi Cuui, Yifan Xu, Dongrui Wu
    http://arxiv.org/abs/1909.11456v1

    • [cs.IR]Neighborhood-Enhanced and Time-Aware Model for Session-based Recommendation
    Yang Lv, Liangsheng Zhuang, Pengyu Luo
    http://arxiv.org/abs/1909.11252v1

    • [cs.IT]Blind Channel Estimation and Data Detection with Unknown Modulation and Coding Scheme
    Yu Liu, Fanggang Wang
    http://arxiv.org/abs/1909.11306v1

    • [cs.IT]Context-Aware Decentralized Invariant Signaling for Opportunistic Communications
    Jordi Borras, Gregori Vazquez
    http://arxiv.org/abs/1909.11528v1

    • [cs.IT]Energy Efficiency Maximization Via Joint Sub-Carrier Assignment and Power Control for OFDMA Full Duplex Networks
    Rojin Aslani, Mehdi Rasti, Ata Khalili
    http://arxiv.org/abs/1909.11160v1

    • [cs.IT]Multiple-Rate Channel Codes in $\texttt{GF}(p{2}})$
    R. S. Raja Durai, Ashwini Kumar
    http://arxiv.org/abs/1909.11296v1

    • [cs.IT]On the Contact and Nearest-Neighbor Distance Distributions for the n-Dimensional Matern Cluster Process
    Kaushlendra Pandey, Harpreet S. Dhillon, Abhishek K. Gupta
    http://arxiv.org/abs/1909.11422v1

    • [cs.IT]On the Information Leakage in Private Information Retrieval Systems
    Tao Guo, Ruida Zhou, Chao Tian
    http://arxiv.org/abs/1909.11605v1

    • [cs.IT]One-shot achievability and converse bounds of Gaussian random coding in AWGN channels under covert constraints
    Xinchun Yu, Shuangqin Wei, Yuan Luo
    http://arxiv.org/abs/1909.11324v1

    • [cs.IT]Power-Imbalanced Low-Density Signatures (LDS) From Eisenstein Numbers
    Zilong Liu, Pei Xiao, Zeina Mheich
    http://arxiv.org/abs/1909.11379v1

    • [cs.IT]Three Dimensional Sums of Character Gabor Systems
    Kung-Ching Lin
    http://arxiv.org/abs/1909.11561v1

    • [cs.LG]A Self-consistent-field Iteration for Orthogonal Canonical Correlation Analysis
    Leihong Zhang, Li Wang, Zhaojun Bai, Ren-cang Li
    http://arxiv.org/abs/1909.11527v1

    • [cs.LG]Adversarial Variational Domain Adaptation
    Manuel Pérez-Carrasco, Guillermo Cabrera-Vives, Pavlos Protopapas, Nicolás Astorga, Marouan Belhaj
    http://arxiv.org/abs/1909.11651v1

    • [cs.LG]Asymptotics of Wide Networks from Feynman Diagrams
    Ethan Dyer, Guy Gur-Ari
    http://arxiv.org/abs/1909.11304v1

    • [cs.LG]Attention-based Deep Tropical Cyclone Rapid Intensification Prediction
    Ching-Yuan Bai, Buo-Fu Chen, Hsuan-Tien Lin
    http://arxiv.org/abs/1909.11616v1

    • [cs.LG]Avoidance Learning Using Observational Reinforcement Learning
    David Venuto, Leonard Boussioux, Junhao Wang, Rola Dali, Jhelum Chakravorty, Yoshua Bengio, Doina Precup
    http://arxiv.org/abs/1909.11228v1

    • [cs.LG]CLN2INV: Learning Loop Invariants with Continuous Logic Networks
    Gabriel Ryan, Justin Wong, Jianan Yao, Ronghui Gui, Suman Jana
    http://arxiv.org/abs/1909.11542v1

    • [cs.LG]Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network
    Taiji Suzuki
    http://arxiv.org/abs/1909.11274v1

    • [cs.LG]Decoder Choice Network for Meta-Learning
    Jialin Liu, Fei Chao, Longzhi Yang, Chih-Min Lin, Qiang Shen
    http://arxiv.org/abs/1909.11446v1

    • [cs.LG]Deep Generative Model for Sparse Graphs using Text-Based Learning with Augmentation in Generative Examination Networks
    Ruud van Deursen, Guillaume Godin
    http://arxiv.org/abs/1909.11472v1

    • [cs.LG]Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders
    Matthew Willetts, Stephen Roberts, Chris Holmes
    http://arxiv.org/abs/1909.11501v1

    • [cs.LG]Domain-invariant Learning using Adaptive Filter Decomposition
    Ze Wang, Xiuyuan Cheng, Guillermo Sapiro, Qiang Qiu
    http://arxiv.org/abs/1909.11285v1

    • [cs.LG]Exascale Deep Learning for Scientific Inverse Problems
    Nouamane Laanait, Joshua Romero, Junqi Yin, M. Todd Young, Sean Treichler, Vitalii Starchenko, Albina Borisevich, Alex Sergeev, Michael Matheson
    http://arxiv.org/abs/1909.11150v1

    • [cs.LG]Gap Aware Mitigation of Gradient Staleness
    Saar Barkai, Ido Hakimi, Assaf Schuster
    http://arxiv.org/abs/1909.10802v2

    • [cs.LG]Graph Neural Reasoning May Fail in Proving Boolean Unsatisfiability
    Ziliang Chen, Zhanfu Yang
    http://arxiv.org/abs/1909.11588v1

    • [cs.LG]Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting
    Tanwi Mallick, Prasanna Balaprakash, Eric Rask, Jane Macfarlane
    http://arxiv.org/abs/1909.11197v1

    • [cs.LG]HaarPooling: Graph Pooling with Compressive Haar Basis
    Yu Guang Wang, Ming Li, Zheng Ma, Guido Montufar, Xiaosheng Zhuang, Yanan Fan
    http://arxiv.org/abs/1909.11580v1

    • [cs.LG]IFR-Net: Iterative Feature Refinement Network for Compressed Sensing MRI
    Yiling Liu, Qiegen Liu, Minghui Zhang, Qingxin Yang, Shanshan Wang, Dong Liang
    http://arxiv.org/abs/1909.10856v2

    • [cs.LG]Input complexity and out-of-distribution detection with likelihood-based generative models
    Joan Serrà, David Álvarez, Vicenç Gómez, Olga Slizovskaia, José F. Núñez, Jordi Luque
    http://arxiv.org/abs/1909.11480v1

    • [cs.LG]Learning in the Machine: To Share or Not to Share?
    Jordan Ott, Erik Linstead, Nicholas LaHaye, Pierre Baldi
    http://arxiv.org/abs/1909.11483v1

    • [cs.LG]Matrix Sketching for Secure Collaborative Machine Learning
    Shusen Wang
    http://arxiv.org/abs/1909.11201v1

    • [cs.LG]Mining Human Mobility Data to Discover Locations and Habits
    Thiago Andrade, Brais Cancela, João Gama
    http://arxiv.org/abs/1909.11406v1

    • [cs.LG]Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models
    Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang
    http://arxiv.org/abs/1909.11299v1

    • [cs.LG]Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks
    Tianyu Pang, Kun Xu, Jun Zhu
    http://arxiv.org/abs/1909.11515v1

    • [cs.LG]Modular Deep Reinforcement Learning with Temporal Logic Specifications
    Lim Zun Yuan, Mohammadhosein Hasanbeig, Alessandro Abate, Daniel Kroening
    http://arxiv.org/abs/1909.11591v1

    • [cs.LG]Neural networks are $\textit{a priori}$ biased towards Boolean functions with low entropy
    Chris Mingard, Joar Skalse, Guillermo Valle-Pérez, David Martínez-Rubio, Vladimir Mikulik, Ard A. Louis
    http://arxiv.org/abs/1909.11522v1

    • [cs.LG]Off-Policy Actor-Critic with Shared Experience Replay
    Simon Schmitt, Matteo Hessel, Karen Simonyan
    http://arxiv.org/abs/1909.11583v1

    • [cs.LG]On Understanding Knowledge Graph Representation
    Carl Allen, Ivana Balazevic, Timothy M. Hospedales
    http://arxiv.org/abs/1909.11611v1

    • [cs.LG]Online Non-Monotone DR-submodular Maximization
    Nguyen Kim Thang, Abhinav Srivastav
    http://arxiv.org/abs/1909.11426v1

    • [cs.LG]Online Semi-Supervised Concept Drift Detection with Density Estimation
    Chang How Tan, Vincent CS Lee, Mahsa Salehi
    http://arxiv.org/abs/1909.11251v1

    • [cs.LG]PCMC-Net: Feature-based Pairwise Choice Markov Chains
    Alix Lhéritier
    http://arxiv.org/abs/1909.11553v1

    • [cs.LG]Pre-training as Batch Meta Reinforcement Learning with tiMe
    Quan Vuong, Shuang Liu, Minghua Liu, Kamil Ciosek, Hao Su, Henrik Iskov Christensen
    http://arxiv.org/abs/1909.11373v1

    • [cs.LG]PyDEns: a Python Framework for Solving Differential Equations with Neural Networks
    Alexander Koryagin, Roman Khudorozkov, Sergey Tsimfer
    http://arxiv.org/abs/1909.11544v1

    • [cs.LG]Reducing Transformer Depth on Demand with Structured Dropout
    Angela Fan, Edouard Grave, Armand Joulin
    http://arxiv.org/abs/1909.11556v1

    • [cs.LG]Regularising Deep Networks with DGMs
    Matthew Willetts, Alexander Camuto, Stephen Roberts, Chris Holmes
    http://arxiv.org/abs/1909.11507v1

    • [cs.LG]Scale-Equivariant Neural Networks with Decomposed Convolutional Filters
    Wei Zhu, Qiang Qiu, Robert Calderbank, Guillermo Sapiro, Xiuyuan Cheng
    http://arxiv.org/abs/1909.11193v1

    • [cs.LG]Semi-supervised classification on graphs using explicit diffusion dynamics
    Robert L. Peach, Alexis Arnaudon, Mauricio Barahona
    http://arxiv.org/abs/1909.11117v1

    • [cs.LG]Sign Language Recognition Analysis using Multimodal Data
    Al Amin Hosain, Panneer Selvam Santhalingam, Parth Pathak, Jana Kosecka, Huzefa Rangwala
    http://arxiv.org/abs/1909.11232v1

    • [cs.LG]Supervised Vector Quantized Variational Autoencoder for Learning Interpretable Global Representations
    Yifan Xue, Michael Ding, Xinghua Lu
    http://arxiv.org/abs/1909.11124v1

    • [cs.LG]Switched linear projections and inactive state sensitivity for deep neural network interpretability
    Lech Szymanski, Brendan McCane, Craig Atkinson
    http://arxiv.org/abs/1909.11275v1

    • [cs.LG]Synthetic Data for Deep Learning
    Sergey I. Nikolenko
    http://arxiv.org/abs/1909.11512v1

    • [cs.LG]Teacher-Student Learning Paradigm for Tri-training: An Efficient Method for Unlabeled Data Exploitation
    Yash Bhalgat, Zhe Liu, Pritam Gundecha, Jalal Mahmud, Amita Misra
    http://arxiv.org/abs/1909.11233v1

    • [cs.LG]The Dynamical Gaussian Process Latent Variable Model in the Longitudinal Scenario
    Thanh Le, Vasant Honavar
    http://arxiv.org/abs/1909.11630v1

    • [cs.LG]When to Intervene: Detecting Abnormal Mood using Everyday Smartphone Conversations
    John Gideon, Katie Matton, Steve Anderau, Melvin G McInnis, Emily Mower Provost
    http://arxiv.org/abs/1909.11248v1

    • [cs.LG]Wider Networks Learn Better Features
    Dar Gilboa, Guy Gur-Ari
    http://arxiv.org/abs/1909.11572v1

    • [cs.MA]$α^α$-Rank: Scalable Multi-agent Evaluation through Evolution
    Yaodong Yang, Rasul Tutunov, Phu Sakulwongtana, Haitham Bou Ammar, Jun Wang
    http://arxiv.org/abs/1909.11628v1

    • [cs.NE]Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space
    AkshatKumar Nigam, Pascal Friederich, Mario Krenn, Alán Aspuru-Guzik
    http://arxiv.org/abs/1909.11655v1

    • [cs.NE]Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network
    Timo C. Wunderlich, Akos F. Kungl, Eric Müller, Johannes Schemmel, Mihai Petrovici
    http://arxiv.org/abs/1909.11145v1

    • [cs.NI]20 Years of Evolution from Cognitive to Intelligent Communications
    Zhijin Qin, Xiangwei Zhou, Lin Zhang, Yue Gao, Ying-Chang Liang, Geoffrey Ye Li
    http://arxiv.org/abs/1909.11562v1

    • [cs.NI]A Predictive On-Demand Placement of UAV Base Stations Using Echo State Network
    Haoran Peng, Chao Chen, Chuan-Chi Lai, Li-Chun Wang, Zhu Han
    http://arxiv.org/abs/1909.11598v1

    • [cs.OS]SIVSHM: Secure Inter-VM Shared Memory
    Shesha Sreenivasamurthy, Ethan Miller
    http://arxiv.org/abs/1909.10377v1

    • [cs.RO]ARCSnake: An Archimedes’ Screw-Propelled, Reconfigurable Robot Snake for Complex Environments
    Dimitri A. Schreiber, Florian Richter, Andrew Bilan, Peter V. Gavrilov, Casey H. Price, Kalind C. Carpenter, Michael C. Yip
    http://arxiv.org/abs/1909.11641v1

    • [cs.RO]Accept Synthetic Objects as Real: End-to-End Training of Attentive Deep Visuomotor Policies for Manipulation in Clutter
    Pooya Abolghasemi, Ladislau Bölöni
    http://arxiv.org/abs/1909.11128v1

    • [cs.RO]Automatic Snake Gait Generation Using Model Predictive Control
    Emily Hannigan, Bing Song, Gagan Khandate, Maximilian Haas Heger, Ji Yin, Matei Ciocarlie
    http://arxiv.org/abs/1909.11204v1

    • [cs.RO]C-3PO: Cyclic-Three-Phase Optimization for Human-Robot Motion Retargeting based on Reinforcement Learning
    Taewoo Kim, Joo-Haeng Lee
    http://arxiv.org/abs/1909.11303v1

    • [cs.RO]CAGE: Context-Aware Grasping Engine
    Weiyu Liu, Angel Daruna, Sonia Chernova
    http://arxiv.org/abs/1909.11142v1

    • [cs.RO]Contact-Aware Controller Design for Complementarity Systems
    Alp Aydinoglu, Victor M. Preciado, Michael Posa
    http://arxiv.org/abs/1909.11221v1

    • [cs.RO]Deep Dynamics Models for Learning Dexterous Manipulation
    Anusha Nagabandi, Kurt Konoglie, Sergey Levine, Vikash Kumar
    http://arxiv.org/abs/1909.11652v1

    • [cs.RO]Human-in-the-loop Robotic Manipulation Planning for Collaborative Assembly
    Mohamed Raessa, Jimmy Chi Yin Chen, Weiwei Wan, Kensuke Harada
    http://arxiv.org/abs/1909.11280v1

    • [cs.RO]Learning to Seek: Autonomous Source Seeking with Deep Reinforcement Learning Onboard a Nano Drone Microcontroller
    Bardienus P. Duisterhof, Srivatsan Krishnan, Jonathan J. Cruz, Colby R. Banbury, William Fu, Aleksandra Faust, Guido C. H. E. de Croon, Vijay Janapa Reddi
    http://arxiv.org/abs/1909.11236v1

    • [cs.RO]Leveraging the Template and Anchor Framework for Safe, Online Robotic Gait Design
    Jinsun Liu, Pengcheng Zhao, Zhenyu Gan, Matthew Johnson-Roberson, Ram Vasudevan
    http://arxiv.org/abs/1909.11125v1

    • [cs.RO]Minimal Work: A Grasp Quality Metric for Deformable Hollow Objects
    Jingyi Xu, Michael Danielczuk, Jeff Ichnowski, Jeffrey Mahler, Eckehard Steinbach, Ken Goldberg
    http://arxiv.org/abs/1909.11226v1

    • [cs.RO]Modeling and Experimental Validation of the Mechanics of a Wheeled Non-Holonomic Robot Capable of Enabling Homeostasis
    Jeremy Epps, Eric Feron, Mark Mote
    http://arxiv.org/abs/1909.11653v1

    • [cs.RO]Motion Estimation in Occupancy Grid Maps in Stationary Settings Using Recurrent Neural Networks
    Marcel Schreiber, Vasileios Belagiannis, Claudius Glaeser, Klaus Dietmayer
    http://arxiv.org/abs/1909.11387v1

    • [cs.RO]Negotiation-based Human-Robot Collaboration via Augmented Reality
    Kishan Chandan, Xiang Li, Shiqi Zhang
    http://arxiv.org/abs/1909.11227v1

    • [cs.RO]OCTNet: Trajectory Generation in New Environments from Past Experiences
    Weiming Zhi, Tin Lai, Lionel Ott, Gilad Francis, Fabio Ramos
    http://arxiv.org/abs/1909.11337v1

    • [cs.RO]Probabilistic Data Association via Mixture Models for Robust Semantic SLAM
    Kevin Doherty, David Baxter, Edward Schneeweiss, John Leonard
    http://arxiv.org/abs/1909.11213v1

    • [cs.RO]ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots
    Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar
    http://arxiv.org/abs/1909.11639v1

    • [cs.RO]Robust Semi-Direct Monocular Visual Odometry Using Edge and Illumination-Robust Cost
    Xiaolong Wu, Cedric Pradalier
    http://arxiv.org/abs/1909.11362v1

    • [cs.RO]Towards Variable Assistance for Lower Body Exoskeletons
    Thomas Gurriet, Maegan Tucker, Alexis Duburcq, Guilhem Boeris, Aaron D. Ames
    http://arxiv.org/abs/1909.11188v1

    • [cs.SD]High Fidelity Speech Synthesis with Adversarial Networks
    Mikołaj Bińkowski, Jeff Donahue, Sander Dieleman, Aidan Clark, Erich Elsen, Norman Casagrande, Luis C. Cobo, Karen Simonyan
    http://arxiv.org/abs/1909.11646v1

    • [cs.SD]HumanGAN: generative adversarial network with human-based discriminator and its evaluation in speech perception modeling
    Kazuki Fujii, Yuki Saito, Shinnosuke Takamichi, Yukino Baba, Hiroshi Saruwatari
    http://arxiv.org/abs/1909.11391v1

    • [cs.SE]Software Engineering Meets Deep Learning: A Literature Review
    Fabio Ferreira, Luciana Lourdes Silva, Marco Tulio Valente
    http://arxiv.org/abs/1909.11436v1

    • [cs.SI]Decentralized Trust Management: Risk Analysis and Trust Aggregation
    Xinxin Fan, Ling Liu, Rui Zhang, Quanliang Jing, Jingping Bi
    http://arxiv.org/abs/1909.11355v1

    • [cs.SI]Mining user interaction patterns in the darkweb to predict enterprise cyber incidents
    Soumajyoti Sarkar, Mohammad Almukaynizi, Jana Shakarian, Paulo Shakarian
    http://arxiv.org/abs/1909.11592v1

    • [eess.AS]Improving Robustness In Speaker Identification Using A Two-Stage Attention Model
    Yanpei Shi, Qiang Huang, Thomas Hain
    http://arxiv.org/abs/1909.11200v1

    • [eess.IV]Augmenting the Pathology Lab: An Intelligent Whole Slide Image Classification System for the Real World
    Julianna D. Ianni, Rajath E. Soans, Sivaramakrishnan Sankarapandian, Ramachandra Vikas Chamarthi, Devi Ayyagari, Thomas G. Olsen, Michael J. Bonham, Coleman C. Stavish, Kiran Motaparthi, Clay J. Cockerell, Theresa A. Feeser, Jason B. Lee
    http://arxiv.org/abs/1909.11212v1

    • [eess.IV]Automated identification of neural cells in the multi-photon images using deep-neural networks
    Si-Baek Seong, Hae-Jeong Park
    http://arxiv.org/abs/1909.11269v1

    • [eess.IV]Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging
    Ayush Singh, Seyed Sadegh Mohseni Salehi, Ali Gholipour
    http://arxiv.org/abs/1909.11625v1

    • [eess.IV]Deep learning vessel segmentation and quantification of the foveal avascular zone using commercial and prototype OCT-A platforms
    Morgan Heisler, Forson Chan, Zaid Mammo, Chandrakumar Balaratnasingam, Pavle Prentasic, Gavin Docherty, MyeongJin Ju, Sanjeeva Rajapakse, Sieun Lee, Andrew Merkur, Andrew Kirker, David Albiani, David Maberley, K. Bailey Freund, Mirza Faisal Beg, Sven Loncaric, Marinko V. Sarunic, Eduardo V. Navajas
    http://arxiv.org/abs/1909.11289v1

    • [eess.IV]Deformable Non-local Network For Video Super-Resolution
    Hua Wang, Dewei Su, Longcun Jin, Chuangchuang Liu
    http://arxiv.org/abs/1909.10692v1

    • [eess.IV]Intelligent image synthesis to attack a segmentation CNN using adversarial learning
    Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, Daniel Rueckert
    http://arxiv.org/abs/1909.11167v1

    • [eess.IV]Non-imaging single-pixel sensing with optimized binary modulation
    Hao Fu, Liheng Bian, Jun Zhang
    http://arxiv.org/abs/1909.11498v1

    • [eess.IV]Towards continuous learning for glioma segmentation with elastic weight consolidation
    Karin van Garderen, Sebastian van der Voort, Fatih Incekara, Marion Smits, Stefan Klein
    http://arxiv.org/abs/1909.11479v1

    • [eess.IV]mustGAN: Multi-Stream Generative Adversarial Networks for MR Image Synthesis
    Mahmut Yurt, Salman Ul Hassan Dar, Aykut Erdem, Erkut Erdem, Tolga Çukur
    http://arxiv.org/abs/1909.11504v1

    • [eess.SP]Optimally Compressed Nonparametric Online Learning
    Alec Koppel, Amrit Singh Bedi, Ketan Rajawat, Brian M. Sadler
    http://arxiv.org/abs/1909.11555v1

    • [eess.SY]Efficient Multi-Agent Trajectory Planning with Feasibility Guarantee using Relative Bernstein Polynomial
    Jungwon Park, Junha Kim, Inkyu Jang, H. Jin Kim
    http://arxiv.org/abs/1909.10219v1

    • [math.ST]Exact confidence interval for generalized Flajolet-Martin algorithms
    Giacomo Aletti
    http://arxiv.org/abs/1909.11564v1

    • [math.ST]Stationarity and Moment Properties of some Multivariate Count Autoregressions
    Zinsou Max Debaly, Lionel Truquet
    http://arxiv.org/abs/1909.11392v1

    • [physics.soc-ph]Inequality is rising where social network segregation interacts with urban topology
    Gergő Tóth, Johannes Wachs, Riccardo Di Clemente, Ákos Jakobi, Bence Ságvári, János Kertész, Balázs Lengyel
    http://arxiv.org/abs/1909.11414v1

    • [physics.soc-ph]Mobile Phone Data for Children on the Move: Challenges and Opportunities
    Vedran Sekara, Elisa Omodei, Laura Healy, Jan Beise, Claus Hansen, Danzhen You, Saskia Blume, Manuel Garcia-Herranz
    http://arxiv.org/abs/1909.11190v1

    • [q-bio.QM]Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile health data
    Kathy Li, Iñigo Urteaga, Chris H. Wiggins, Anna Druet, Amanda Shea, Virginia J. Vitzthum, Noémie Elhadad
    http://arxiv.org/abs/1909.11211v1

    • [q-fin.CP]Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimensions
    Yangang Chen, Justin W. L. Wan
    http://arxiv.org/abs/1909.11532v1

    • [quant-ph]Practical route to entanglement-enhanced communication over noisy bosonic channels
    Haowei Shi, Zheshen Zhang, Quntao Zhuang
    http://arxiv.org/abs/1909.11112v1

    • [stat.AP]Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis
    C. Gary Mena, Arno De Caigny, Kristof Coussement, Koen W. De Bock, Stefan Lessmann
    http://arxiv.org/abs/1909.11114v1

    • [stat.AP]Selecting a Scale for Spatial Confounding Adjustment
    Joshua P. Keller, Adam A. Szpiro
    http://arxiv.org/abs/1909.11161v1

    • [stat.CO]Real time analysis of epidemic data
    Jessica Welding, Peter Neal
    http://arxiv.org/abs/1909.11560v1

    • [stat.ME]Survival analysis as a classification problem
    Chenyang Zhong, Robert Tibshirani
    http://arxiv.org/abs/1909.11171v1

    • [stat.ME]Testing for Association in Multi-View Network Data
    Lucy L. Gao, Daniela Witten, Jacob Bien
    http://arxiv.org/abs/1909.11640v1

    • [stat.ML]A Generative Model for Molecular Distance Geometry
    Gregor N. C. Simm, José Miguel Hernández-Lobato
    http://arxiv.org/abs/1909.11459v1

    • [stat.ML]Classification Logit Two-sample Testing by Neural Networks
    Xiuyuan Cheng, Alexander Cloninger
    http://arxiv.org/abs/1909.11298v1

    • [stat.ML]Determining offshore wind installation times using machine learning and open data
    Bo Tranberg, Kasper Koops Kratmann, Jason Stege
    http://arxiv.org/abs/1909.11313v1

    • [stat.ML]Hierarchical Probabilistic Model for Blind Source Separation via Legendre Transformation
    Simon Luo, Lamiae Azizi, Mahito Sugiyama
    http://arxiv.org/abs/1909.11294v1

    • [stat.ML]Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi’s Entropy and Tensor Kernels
    Kristoffer Wickstrøm, Sigurd Løkse, Michael Kampffmeyer, Shujian Yu, Jose Principe, Robert Jenssen
    http://arxiv.org/abs/1909.11396v1

    • [stat.ML]Modelling the influence of data structure on learning in neural networks
    Sebastian Goldt, Marc Mézard, Florent Krzakala, Lenka Zdeborová
    http://arxiv.org/abs/1909.11500v1

    • [stat.ML]Simple and Almost Assumption-Free Out-of-Sample Bound for Random Feature Mapping
    Shusen Wang
    http://arxiv.org/abs/1909.11207v1

    • [stat.ML]Structured Graph Learning Via Laplacian Spectral Constraints
    Sandeep Kumar, Jiaxi Ying, Jos’e Vin’icius de M. Cardoso, Daniel P. Palomar
    http://arxiv.org/abs/1909.11594v1